Harnessing Generative AI for a Value-Based Revolution

The Parallel Path of Innovation: Generative AI and the Internet

The unveiling of AI models by organizations like OpenAI in 2022/2023 marks a pivotal democratization of a new technology. Generative AI will create innovation on a scale not witnessed since the introduction of publicly accessible internet in 1991. Nowhere is the impact more profound than the healthcare sector, where open-access AI research is accelerating innovation and widespread accessibility and allowing healthcare providers of all sizes to tap into AI's potential, enhancing disease detection and prediction of patient outcomes.

Deeper parallels between the historic path carved by the internet and the ongoing journey of generative AI offer compelling insights into how this technology could reshape medical practices, business models and patient experiences. Most notably, it underlines the opportunities to further the central tenets of value-based care, a healthcare delivery model that emphasizes the quality of patient outcomes rather than the volume of services provided, at a speed and scale beyond any effort today.

Generative AI has transitioned from a conceptual stage where it existed only in academic research to a point of refinement and standardization, much like how the internet evolved from the creation of ARPANET to the standards of TCP/IP. Having moved beyond the concept stage, generative AI models have been developed into working, standardized algorithms.

The Last Step: Commercialization of Generative AI

As generative AI evolves further, the creation of more user-friendly tools and applications will become crucial. Much like how early internet browsers democratized information access, intuitive interfaces will do the same for AI technology, particularly in the healthcare sector. These platforms will revolutionize the support provided to health professionals in every way, facilitating everything from the use of AI-augmented point of care workflows to enabling real-time, predictive alerts for patient deterioration. This transformation will shift healthcare delivery from a reactive approach to a proactive one, empowering providers to anticipate and address issues before they escalate.

While the specific use cases of generative AI commercialization in healthcare are infinite, it is important to discern current reality from aspirational thinking of what this could potentially achieve in the future. In value-based care, addressing physician burnout is a particular benefit of generative AI worth exploring. Given that physician burnout is most often attributed to excessive documentation requirements, there is a growing need for innovative generative AI solutions to alleviate this burden and restore the joy of practicing medicine. It has been reported that a family physician would need 21.7 hours per work day to deliver recommended care to a panel of 2500 patients1 and that 62% of a doctors’ time caring for an individual patient is spent outside of the patient encounter documented in the EMR2. To ameliorate this immense documentation requirement, there is a current use case underway where ambient listening devices are paired with Natural Language Processing/Voice Recognition and generative AI technologies to automatically create a written progress note during an office visit encounter. An application of this generative AI-driven technology has been shown to save physicians an average of three hours a day and costs around one-sixth the cost of human medical scribes3.

Just as e-commerce revolutionized retail, generative AI will fuel capital infusion into the healthcare sector. Likewise, AI commercialization will play a catalytic role in the pivot from fee-for-service to value-based care. The tenets of value-based care lie in offering quality care that is also cost-effective, focusing on patient outcomes rather than procedures performed. Generative AI has the potential to enable such a shift on a grand scale. It could help identify high-risk patients early, prevent avoidable hospitalizations, suggest follow-ups and personalized treatment plans, and consistently monitor and predict outcomes. By forecasting healthcare issues before they escalate into expensive procedures, AI can lead to a system that rewards prevention and effective early treatment. AI offers scale at a low cost to a prevention-driven model in value-based care - shareholders, entrepreneurs, and business owners will see the business opportunity in front of them.

The Future State: Generative AI and Value-Based Care 

With generative AI models projected to become at least 30 times more powerful in just five years (and 1,000 times more powerful in a mere decade)4, there is exponential potential for it to catalyze value-based care with the stated CMS goal to have 100% of Medicare fee-for-service beneficiaries in an accountable care relationship by 20305. The doctor-patient relationship of the future will be enabled by generative AI, resulting in improved effectiveness of medical care, patient convenience in obtaining information, and reduced medical expenditures through enhanced patient engagement. Following each virtual or in-person clinical interaction, we will see AI assistants create personalized medical records for patients that are expressed in a more nuanced way that supports improved health literacy and engagement. While physicians remain in the driver’s seat, AI will greatly augment their capacity and will eventually become the backbone of every healthcare encounter, monitoring patients 24/7 with predictive diagnosis, health analysis, recommendations for equitable access to services, and medical expertise. Combined with telemedicine and wearable devices, AI will also solve the challenges of “hospital at home” by offering a safer alternative for lower acuity patients spending days in an inpatient setting.

At Lumeris, we believe these advancements in predictive and data-driven capabilities will accelerate the value-based care adoption curve. Currently, Lumeris' partnerships with healthcare providers oversee the management of over $13 billion in medical expenditures, spanning across risk-based Medicare Advantage, Traditional Medicare, Medicaid, and Commercial populations. Our AI-infused technology stack results in superior quality metrics, enhanced patient experience and physician satisfaction, and notable reductions in the total cost of care in risk-based contracts. Our framework for AI in value-based care focuses on data aggregation, insights generation at the patient- and population-level, augmented clinical intelligence and decision support, and autonomous interactions for consumer and provider engagement along the care journey. We have integrated AI into a broad array of solutions, from creating a private/secure version of the chat capability to improve productivity, to improving how we identify chronic conditions and drive the most effective interventions.

AI and LLM capabilities are now being democratized more than ever, and we see generative AI as an especially meaningful opportunity to apply it in areas of high need such as chronic disease management and social determinants of health. In the future, we expect generative AI will accelerate success in value-based care with models being used to detect high risk patients, detect gaps in care, provide evidence, and support physicians in appropriate documentation. Lumeris envisions a future of value-based care that epitomizes the system of care that every doctor wants for their own family, and generative AI will be one of our most powerful tools to personalize medicine, empower patients, and optimize care delivery for a healthier future. 

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Resources:

• For more insights on AI and Value-Based Care, refer to Lumeris’ most recent podcast episode of “Enabling Health Value” with Micky Tripathi, the U.S. National Coordinator for Health IT
• You can also download Lumeris’ most recent whitepaper by Dr. Chris Windham.